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Journal ArticleDOI

User Activity Patterns During Information Search

TLDR
The results show that similar patterns of user activity are observed at both the cognitive and page use levels, and activity patterns are able to distinguish between task types in similar ways and between tasks of different levels of difficulty.
Abstract
Personalization of support for information seeking depends crucially on the information retrieval system's knowledge of the task that led the person to engage in information seeking. Users work during information search sessions to satisfy their task goals, and their activity is not random. To what degree are there patterns in the user activity during information search sessionsq Do activity patterns reflect the user's situation as the user moves through the search task under the influence of his or her task goalq Do these patterns reflect aspects of different types of information-seeking tasksq Could such activity patterns identify contexts within which information seeking takes placeq To investigate these questions, we model sequences of user behaviors in two independent user studies of information search sessions (N = 32 users, 128 sessions, and N = 40 users, 160 sessions). Two representations of user activity patterns are used. One is based on the sequences of page use; the other is based on a cognitive representation of information acquisition derived from eye movement patterns in service of the reading process. One of the user studies considered journalism work tasks; the other concerned background research in genomics using search tasks taken from the TREC Genomics Track. The search tasks differed in basic dimensions of complexity, specificity, and the type of information product (intellectual or factual) needed to achieve the overall task goal. The results show that similar patterns of user activity are observed at both the cognitive and page use levels. The activity patterns at both representation layers are able to distinguish between task types in similar ways and, to some degree, between tasks of different levels of difficulty. We explore relationships between the results and task difficulty and discuss the use of activity patterns to explore events within a search session. User activity patterns can be at least partially observed in server-side search logs. A focus on patterns of user activity sequences may contribute to the development of information systems that better personalize the user's search experience.

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Journal ArticleDOI

Interactive Intent Modeling for Exploratory Search

TL;DR: This work introduces interactive intent modeling, a technique that models a user’s evolving search intents and visualizes them as keywords for interaction to help design personalized systems that support exploratory information seeking and discovery of novel information.
Journal ArticleDOI

Consumer health information and question answering: helping consumers find answers to their health-related information needs

TL;DR: A pilot practical implementation of research needed to help consumers find reliable answers to their health-related questions demonstrates that for most questions the reliable answers exist and can be found automatically with acceptable accuracy.
Journal ArticleDOI

Ctf-ara

TL;DR: An adaptive POI recommendation method by combining check-in and temporal features with user-based collaborative filtering with cosine similarity of different time slots smoothing technique is proposed, which can operate adaptively according to the activity of user.
Journal ArticleDOI

Comparative analysis of relevance feedback methods based on two user studies

TL;DR: The findings suggest that there is no significant difference between the predictive model based on implicit indicators and eye gaze within the context examined, and this can help to develop recommender and personalised systems for recommending documents to users based on their previous interaction with the system.
Journal ArticleDOI

A Decade of NeuroIS Research: Progress, Challenges, and Future Directions

TL;DR: NeuroIS is a field in Information Systems (IS) that makes use of neuroscience and neurophysiological tools and knowledge to better understand the development, adoption, and impact of information and communication technologies as mentioned in this paper.
References
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Book

Information Processing

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